NONINVASIVE DIAGNOSTIC TESTS FOR HELICOBACTER PYLORI INFECTION (REVIEW)
Bibliographic record
Abstract
Jacqueline Pich, PhD, BNurs (Hons I), BSc, is a member of the Cochrane Nursing Care (CNC); and is Lecturer, Faculty of Health, UTS Sydney, Ultimo, New South Wales, Australia. Correspondence to: Jacqueline Pich, PhD, BNurs (Hons I), BSc, Faculty of Health, UTS Sydney, Ultimo, 235 Jones St, Ultimo NSW 2007, Australia ([email protected]). THE OFFICIAL JOURNAL OF THE SOCIETY OF GASTROENTEROLOGY NURSES AND ASSOCIATES, INC. AND THE CANADIAN SOCIETY OF GASTROENTEROLOGY NURSES AND ASSOCIATESDEDICATED TO THE SAFE AND EFFECTIVE PRACTICE OF GASTROENTEROLOGY AND ENDOSCOPY NURSINGThe author declares no conflicts of interest.The Mission of the Cochrane Nursing Care Field (CNCF) is to improve health outcomes through increasing the use of the Cochrane Library and supporting Cochrane's role by providing an evidence base for nurses and related healthcare professionals involved in delivering, leading or researching nursing care. The CNCF produces ‘Cochrane Corner' columns (summaries of recent nursing-care-relevant Cochrane Reviews) that are regularly published in collaborating nursing-care-related journals. Information on the processes this Field has developed can be accessed at: http://cncf.cochrane.org/evidence-transfer-program-review-summaries
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".